UTF8 Ignore read file errors
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Dockerfile+ChatGLM
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Dockerfile+ChatGLM
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# How to build | 如何构建: docker build -t gpt-academic --network=host -f Dockerfile+ChatGLM .
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# How to run | 如何运行 (1) 直接运行: docker run --rm -it --net=host gpt-academic
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# How to run | 如何运行 (2) 我想运行之前进容器做一些调整: docker run --rm -it --net=host --gpu=all gpt-academic bash
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# 从NVIDIA源,从而支持显卡运损(检查宿主的nvidia-smi中的cuda版本必须>=11.3)
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FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
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ARG useProxyNetwork=''
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RUN apt-get update
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RUN apt-get install -y curl proxychains curl
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RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
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# 配置代理网络(构建Docker镜像时使用)
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# # comment out below if you do not need proxy network | 如果不需要翻墙 - 从此行向下删除
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RUN $useProxyNetwork curl cip.cc
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RUN sed -i '$ d' /etc/proxychains.conf
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RUN sed -i '$ d' /etc/proxychains.conf
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RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
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ARG useProxyNetwork=proxychains
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# # comment out above if you do not need proxy network | 如果不需要翻墙 - 从此行向上删除
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# use python3 as the system default python
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RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
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# 下载分支
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WORKDIR /gpt
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RUN $useProxyNetwork git clone https://github.com/binary-husky/chatgpt_academic.git -b v3.0
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WORKDIR /gpt/chatgpt_academic
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RUN $useProxyNetwork python3 -m pip install -r requirements.txt
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RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
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RUN $useProxyNetwork python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
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# 为chatgpt-academic配置代理和API-KEY (非必要 可选步骤)
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RUN echo ' \n\
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API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
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USE_PROXY = True \n\
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proxies = { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } ' >> config_private.py
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# 预热CHATGLM参数(非必要 可选步骤)
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RUN echo ' \n\
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from transformers import AutoModel, AutoTokenizer \n\
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chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) \n\
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chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float() ' >> warm_up_chatglm.py
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RUN python3 -u warm_up_chatglm.py
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# 启动
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CMD ["python3", "-u", "main.py"]
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@ -45,7 +45,7 @@ def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
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pfg = PaperFileGroup()
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for index, fp in enumerate(file_manifest):
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with open(fp, 'r', encoding='utf-8') as f:
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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# 定义注释的正则表达式
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comment_pattern = r'%.*'
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@ -44,7 +44,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
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pfg = PaperFileGroup()
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for index, fp in enumerate(file_manifest):
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with open(fp, 'r', encoding='utf-8') as f:
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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# 定义注释的正则表达式
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comment_pattern = r'%.*'
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@ -49,7 +49,7 @@ def 全项目切换英文(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_
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# 第4步:随便显示点什么防止卡顿的感觉
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for index, fp in enumerate(file_manifest):
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# if 'test_project' in fp: continue
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with open(fp, 'r', encoding='utf-8') as f:
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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i_say_show_user =f'[{index}/{len(file_manifest)}] 接下来请将以下代码中包含的所有中文转化为英文,只输出转化后的英文代码,请用代码块输出代码: {os.path.abspath(fp)}'
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i_say_show_user_buffer.append(i_say_show_user)
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@ -72,7 +72,7 @@ def 全项目切换英文(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_
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if index > 10:
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time.sleep(60)
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print('Openai 限制免费用户每分钟20次请求,降低请求频率中。')
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with open(fp, 'r', encoding='utf-8') as f:
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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i_say_template = lambda fp, file_content: f'接下来请将以下代码中包含的所有中文转化为英文,只输出代码,文件名是{fp},文件代码是 ```{file_content}```'
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try:
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@ -68,7 +68,7 @@ def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbo
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print('begin analysis on:', file_manifest)
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for index, fp in enumerate(file_manifest):
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if ".tex" in fp:
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with open(fp, 'r', encoding='utf-8') as f:
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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if ".pdf" in fp.lower():
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file_content = readPdf(fp)
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@ -7,7 +7,7 @@ def 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
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import time, os
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print('begin analysis on:', file_manifest)
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for index, fp in enumerate(file_manifest):
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with open(fp, 'r', encoding='utf-8') as f:
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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i_say = f'请对下面的程序文件做一个概述,并对文件中的所有函数生成注释,使用markdown表格输出结果,文件名是{os.path.relpath(fp, project_folder)},文件内容是 ```{file_content}```'
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@ -14,7 +14,7 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
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############################## <第一步,逐个文件分析,多线程> ##################################
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for index, fp in enumerate(file_manifest):
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with open(fp, 'r', encoding='utf-8') as f:
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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prefix = "接下来请你逐文件分析下面的工程" if index==0 else ""
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i_say = prefix + f'请对下面的程序文件做一个概述文件名是{os.path.relpath(fp, project_folder)},文件代码是 ```{file_content}```'
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import time, glob, os
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print('begin analysis on:', file_manifest)
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for index, fp in enumerate(file_manifest):
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with open(fp, 'r', encoding='utf-8') as f:
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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prefix = "接下来请你逐文件分析下面的论文文件,概括其内容" if index==0 else ""
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